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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Application of Bipartite Networks to the Study of Water Quality

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Autor(es):
Pineda-Pineda, Jair J. [1] ; Martinez-Martinez, C. T. [2, 3] ; Mendez-Bermudez, J. A. [2, 4] ; Munoz-Rojas, Jesus [1] ; Sigarreta, Jose M. [5]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Benemerita Univ Autonoma Puebla BUAP, Inst Ciencias IC, Ctr Invest Ciencias Microbiol CICM, Ecol & Survival Microorganisms Res Grp ESMRG, Lab, Puebla 72570 - Mexico
[2] Benemerita Univ Autonoma Puebla, Inst Fis, Puebla 72570 - Mexico
[3] Univ Zaragoza, Inst Biocomputat & Phys Complex Syst BIFI, Zaragoza 50018 - Spain
[4] Univ Sao Paulo, Inst Ciencias Matemat & Comp, Dept Matemat Aplicada & Estat, Campus Sao Carlos, Caixa Postal 668, BR-13560970 Sao Carlos, SP - Brazil
[5] Univ Autonoma Guerrero, Fac Matemat, Acapulco 39650 - Mexico
Número total de Afiliações: 5
Tipo de documento: Artigo Científico
Fonte: SUSTAINABILITY; v. 12, n. 12 JUN 2020.
Citações Web of Science: 0
Resumo

Water is a basic natural resource for life and the sustainable development of society. Methods to assess water quality in freshwater ecosystems based on environmental quality bioindicators have proven to be low cost, reliable, and can be adapted to ecosystems with well-defined structures. The objective of this paper is to propose an interdisciplinary approach for the assessment of water quality in freshwater ecosystems through bioindicators. From the presence/absence of bioindicator organisms and their sensitivity/tolerance to environmental stress, we constructed a bipartite network,G. In this direction, we propose a new method that combines two research approaches, Graph Theory and Random Matrix Theory (RMT). Through the topological properties of the graphG, we introduce a topological index, calledJP(G), to evaluate the water quality, and we study its properties and relationships with known indices, such as Biological Monitoring Working Party (BMWP) and Shannon diversity (H `). Furthermore, we perform a scaling analysis of random bipartite networks with already specialized parameters for our case study. We validate our proposal for its application in the reservoir of Guajaro, Colombia. The results obtained allow us to infer that the proposed techniques are useful for the study of water quality, since they detect significant changes in the ecosystem. (AU)

Processo FAPESP: 19/06931-2 - Métodos de matrizes aleatórias em redes complexas
Beneficiário:Francisco Aparecido Rodrigues
Linha de fomento: Auxílio à Pesquisa - Pesquisador Visitante - Internacional